Distill Memory

When to Suggest (Moment Detection)

Breakthrough: Extended debugging resolves, user relief ("Finally!", "Aha!"), root cause found

Decision: Compared options, chose with rationale, trade-off resolved

Research: Investigated multiple approaches, conclusion reached, optimal path determined

Twist: Unexpected cause-effect, counterintuitive solution, assumption challenged

Lesson: "Next time do X", preventive measure, pattern recognized

Skip: Routine fixes, work in progress, simple Q&A, generic info

Memory Quality

Good (atomic + actionable):

• "React hooks cleanup must return function. Caused leaks."
• "PostgreSQL over MongoDB: ACID needed for transactions."

Poor: Vague "Fixed bugs", conversation transcript

Tool Usage

{
  "content": "Insight + context for future use",
  "title": "Searchable (50-60 chars)",
  "importance": 0.8,
  "labels": "tech,domain,topic"
}

Content: Outcome/insight focus, include "why", enough context

Importance: 0.8-1.0 major | 0.5-0.7 useful | 0.3-0.4 minor

Labels: 2-4 max, check existing first, lowercase-hyphenated

Suggestion

Timing: After resolution/decision, when user pauses

Pattern: "This [type] seems valuable - [essence]. Distill into memory?"

Frequency: 1-3 per session typical, quality over quantity

Troubleshooting

If the MCP is not installed, you can install it with the following command:

claude mcp add --transport http nowledge-mem http://localhost:14242/mcp --scope user